In a wireless communication system, it is the most important to accurately determine information on a received signal, for the purpose of utilizing a hostile communication area or cognitive radio (CR) technology instead of a communication method that sends predefined information.
In the techniques for automatic modulation recognition of an unknown signal, proposed have mostly been algorithms to extract characteristic of the unknown signal based on a baseband from which a carrier frequency has been removed. Therefore, it is important, to accurately find the carrier frequency of the unknown signal. In other words, automatic modulation recognition techniques have been developed on the assumption that some information favorable to the algorithms is fundamentally known in advance, and particularly, most of the techniques are implemented on the assumption that a carrier frequency is accurately restored. Thus, when a portion of the carrier frequency is remained in an actual environment, the performance of the automatic modulation techniques is degraded, and moreover, efficiency is reduced.
Moreover, generally, an automatic modulation classification technology in which the restoration of a carrier frequency is not performed classifies an unknown signal into a phase shift keying (PSK) class or a frequency shift keying (FSK) class according to the change in a signal level, restores a carrier frequency of the unknown signal, and then uses the modulation recognition techniques.
More specifically, the automatic modulation classification techniques uses information on a signal level and moreover uses a complicated scheme in which an algorithm, for deciding a modulation index “M” is conducted in a frequency domain. Due to this, a complicated and overlapping signal processing is needed to be performed for restoring an unknown signal in an actual environment in which a sampling rate of an automatic modulation recognition system is fixed.